NGP Capital is a global venture capital firm with over $1.2 billion under management investing in US, Europe and China. We back entrepreneurs building growth-stage technology companies within the Enterprise Software, Mobility and Mobile. Our Helsinki office is located at Maria 01.

We’re looking for a Data Engineer to help us build and deploy our internal Data and Analytics platform “Q”. The Q platform is pivotal for our investment team to receive the latest insights on investment prospects, and a key part of our ongoing journey towards data-driven investing. You’ll be working in a small and focused team where you can make a difference.

The bulk of the work will be related to data pipelines and processing, but we value interest in data science, and can provide interesting challenges with Machine Learning tasks as well. We’re treating our project like an internal start-up, and focus on delivering value each day and effectively supporting our business. We leverage GCP managed services where possible, and offer a cutting edge technology stack as well as a no-nonsense environment with minimal bureaucracy.

Key responsibilities:

• Develop data pipelines to ingest data from a variety of data sources, ranging from APIs and flat files to unstructured data scraped from web

• Design and implement optimized data stores and models for different phases of data processing

• Maintain and improve operational data pipelines

• Support (and if interested, also take some responsibility over) development and operationalization of AI & ML initiatives

• Collaborate with external partners in both data engineering and data science initiatives

• Investigate and introduce new technologies to improve current solutions in speed and robustness

• Follow industry trends in data processing and bring in a strong interest in cutting-edge technology

Key requirements:

• Experience in programming scalable and robust data integration workflows with a programming language such as Python or Scala

• Experience of related technologies, such as containers (Docker/Kubernetes), continuous integration, version control, streaming and real-time processing

• Familiarity with microservices architecture and serverless processing

• Familiarity with major cloud platforms, such as AWS, Azure or GCP

• Good knowledge of database design and SQL, understanding of data modelling techniques